This notebook contains a set of analyses for analyzing aboardgamebarrage’s boardgamegeek collection. The bulk of the analysis is focused on building a user-specific predictive model to predict the games that the specified user is likely to own. This enables us to ask questions like, based on the games the user currently owns, what games are a good fit for their collection? What upcoming games are they likely to purchase?
We can look at a basic description of the number of games that the user owns, has rated, has previously owned, etc.
What years has the user owned/rated games from? While we can’t see when a user added or removed a game from their collection, we can look at their collection by the years in which their games were published.
We can look at the most frequent types of categories, mechanics, designers, and artists that appear in a user’s collection.
We’ll examine predictive models trained on a user’s collection for games published through 2020. How many games has the user owned/rated/played in the training set (games prior to 2020)?
username | dataset | period | games_owned | games_rated |
aboardgamebarrage | training | published before 2020 | 306 | 195 |
aboardgamebarrage | validation | published 2020 | 5 | 23 |
aboardgamebarrage | test | published after 2020 | 1 | 10 |
The main outcome we will be modeling for the user is owned, which refers to whether the user currently owns or has a previously owned a game in their collection. Our goal is to train a predictive model to learn the probability that a user will add a game to their collection based on its observable features. This amounts to looking at historical data and looking to find patterns that exist between features of games and games present in the user’s collection.
One of the models we trained was a decision tree, which looks for decision rules that can be used to separate games the user owns from games they don’t. The resulting model produces a decision corresponding to yes or no statements: to explain why the model predicts the user to own game, we start at the top of the tree and follow the rules that were learned from the training data.
Note: the tree below has been further pruned to make it easier to visualize.
Decision trees are highly interpretible models that are easy to train and can identify important interactions and nonlinearities present in the data. Individual trees have the drawback of being less predictive than other common models, but it can be useful to look at them to gain some understanding of key predictors and relationships found in the training data.
We can examine coefficients from another model we trained, which is a logistic regression with elastic net regularization (which I will refer to as a penalized logistic regression). Positive values indicate that a feature increases a user’s probability of owning/rating a game, while negative values indicate a feature decreases the probability. To be precise, the coefficients indicate the effect of a particular feature on the log-odds of a user owning a game.
Why did the model identify these features? We can make density plots of the important features for predicting whether the user owned a game. Blue indicates the density for games owned by the user, while grey indicates the density for games not owned by the user.
Binary predictors can be difficult to see with this visualization, so we can also directly examine the percentage of games in a user’s collection with a predictor vs the percentage of all games with that predictor.
% of Games with Feature | ||||
username | Feature | User_Collection | All_Games | Ratio |
aboardgamebarrage | Asmodee | 15.0% | 2.5% | 6.09 |
aboardgamebarrage | ZMan Games | 6.2% | 1.4% | 4.49 |
aboardgamebarrage | Artist Oliver Freudenreich | 2.3% | 0.6% | 3.64 |
aboardgamebarrage | Dice With Icons | 3.9% | 1.1% | 3.49 |
aboardgamebarrage | Deduction Game | 11.8% | 5.0% | 2.35 |
aboardgamebarrage | Party Game | 18.3% | 9.2% | 1.98 |
aboardgamebarrage | Ravensburger | 4.6% | 2.4% | 1.87 |
aboardgamebarrage | Tile Placement | 7.2% | 8.1% | 0.88 |
aboardgamebarrage | Action Points | 4.6% | 5.2% | 0.87 |
aboardgamebarrage | Dice Rolling | 16.3% | 28.6% | 0.57 |
aboardgamebarrage | Point To Point Movement | 2.3% | 4.3% | 0.53 |
aboardgamebarrage | Novel Based | 0.7% | 2.4% | 0.27 |
aboardgamebarrage | Roll Spin And Move | 1.3% | 6.8% | 0.19 |
aboardgamebarrage | Wargame | 3.3% | 18.9% | 0.17 |
aboardgamebarrage | Simulation | 1.6% | 10.3% | 0.16 |
aboardgamebarrage | Comic Book Strip | 0.0% | 1.6% | 0.00 |
Before predicting games in upcoming years, we can examine how well the model did and what games it liked in the training set. In this case, we used resampling techniques (cross validation) to ensure that the model had not seen a game before making its predictions.
Displaying the 100 games from the training set with the highest probability of ownership, highlighting in blue games the user has owned.
Rank | Published | ID | Name | Pr(Owned) | Owned |
1 | 2018 | 205896 | Rising Sun | 0.948 | no |
2 | 2017 | 233078 | Twilight Imperium: Fourth Edition | 0.907 | yes |
3 | 2008 | 33107 | Senji | 0.694 | yes |
4 | 2016 | 176083 | Hit Z Road | 0.692 | no |
5 | 2014 | 132531 | Roll for the Galaxy | 0.681 | no |
6 | 2015 | 175878 | 504 | 0.632 | no |
7 | 2016 | 205398 | Citadels | 0.628 | no |
8 | 2019 | 286096 | Tapestry | 0.623 | no |
9 | 2017 | 220308 | Gaia Project | 0.605 | no |
10 | 2019 | 285984 | Last Bastion | 0.601 | no |
11 | 2014 | 157403 | Black Fleet | 0.565 | no |
12 | 2012 | 105551 | Archipelago | 0.543 | yes |
13 | 2017 | 195539 | The Godfather: Corleone's Empire | 0.517 | no |
14 | 2016 | 187645 | Star Wars: Rebellion | 0.505 | no |
15 | 2019 | 267304 | Western Empires | 0.488 | no |
16 | 2019 | 189453 | Victorian Masterminds | 0.486 | no |
17 | 2005 | 18258 | Mission: Red Planet | 0.476 | no |
18 | 2000 | 478 | Citadels | 0.472 | no |
19 | 2014 | 151369 | Illegal | 0.433 | no |
20 | 2012 | 104710 | Wiz-War (Eighth Edition) | 0.432 | yes |
21 | 2012 | 120677 | Terra Mystica | 0.431 | no |
22 | 2004 | 12942 | No Thanks! | 0.424 | yes |
23 | 2004 | 9220 | Saboteur | 0.422 | no |
24 | 2017 | 221107 | Pandemic Legacy: Season 2 | 0.407 | no |
25 | 2018 | 255692 | New Frontiers | 0.403 | no |
26 | 2012 | 128882 | The Resistance: Avalon | 0.390 | no |
27 | 1998 | 503 | Through the Desert | 0.387 | yes |
28 | 1986 | 925 | Werewolf | 0.384 | no |
29 | 2009 | 54998 | Cyclades | 0.383 | no |
30 | 2013 | 127024 | Room 25 | 0.381 | no |
31 | 2010 | 63740 | Hotel Samoa | 0.379 | no |
32 | 2014 | 157354 | Five Tribes | 0.377 | no |
33 | 2008 | 37370 | Seii Taishogun | 0.374 | no |
34 | 2017 | 224152 | Hemloch: Dark Promenade | 0.373 | no |
35 | 2018 | 209324 | The World of SMOG: Rise of Moloch | 0.373 | no |
36 | 2009 | 56885 | The Werewolves of Miller's Hollow: The Village | 0.362 | no |
37 | 2006 | 21882 | Blue Moon City | 0.350 | no |
38 | 1997 | 42 | Tigris & Euphrates | 0.346 | no |
39 | 2016 | 206754 | Burke's Gambit | 0.345 | no |
40 | 2012 | 124044 | Tooth & Nail: Factions | 0.340 | no |
41 | 2019 | 270269 | Ninja Academy | 0.336 | no |
42 | 2012 | 117915 | Yedo | 0.335 | no |
43 | 2019 | 266936 | Slyville | 0.333 | no |
44 | 2012 | 131357 | Coup | 0.331 | no |
45 | 2015 | 181304 | Mysterium | 0.329 | yes |
46 | 2016 | 205158 | Codenames: Deep Undercover | 0.329 | no |
47 | 2016 | 167791 | Terraforming Mars | 0.327 | no |
48 | 2018 | 199792 | Everdell | 0.327 | no |
49 | 2019 | 259081 | Machi Koro Legacy | 0.325 | no |
50 | 2017 | 221805 | Breaking Bad: The Board Game | 0.320 | no |
51 | 2019 | 270971 | Era: Medieval Age | 0.320 | yes |
52 | 2014 | 152241 | Ultimate Werewolf | 0.316 | no |
53 | 2019 | 272770 | Ravnica: Inquisition | 0.315 | no |
54 | 2017 | 200847 | Secrets | 0.311 | yes |
55 | 2014 | 148228 | Splendor | 0.298 | yes |
56 | 2017 | 195560 | Wasteland Express Delivery Service | 0.295 | no |
57 | 2017 | 236475 | Best of Werewolves of Miller's Hollow | 0.293 | no |
58 | 2015 | 172563 | Hemloch: Midnight Edition | 0.291 | no |
59 | 2019 | 283294 | Yukon Airways | 0.290 | no |
60 | 2019 | 283863 | The Magnificent | 0.289 | no |
61 | 2004 | 10547 | Betrayal at House on the Hill | 0.288 | no |
62 | 2014 | 158899 | Colt Express | 0.288 | no |
63 | 2001 | 1345 | Genoa | 0.288 | yes |
64 | 2010 | 73439 | Troyes | 0.286 | yes |
65 | 2015 | 176920 | Mission: Red Planet (Second Edition) | 0.284 | yes |
66 | 2017 | 231215 | Merchants of Muziris | 0.284 | yes |
67 | 2019 | 232956 | Omen: Fires in the East | 0.284 | no |
68 | 1998 | 20832 | Halli Galli Junior | 0.284 | no |
69 | 2013 | 124380 | Ladies & Gentlemen | 0.282 | no |
70 | 2008 | 38159 | Ultimate Werewolf: Ultimate Edition | 0.279 | no |
71 | 2018 | 313010 | Cosmic Encounter: 42nd Anniversary Edition | 0.279 | no |
72 | 2000 | 475 | Taj Mahal | 0.277 | yes |
73 | 1999 | 88 | Torres | 0.276 | no |
74 | 2017 | 174430 | Gloomhaven | 0.275 | no |
75 | 2016 | 203818 | Akua | 0.269 | no |
76 | 1990 | 2944 | Halli Galli | 0.267 | no |
77 | 2011 | 109548 | Hemloch | 0.266 | no |
78 | 2016 | 195518 | Crazy Karts | 0.263 | no |
79 | 1995 | 13 | Catan | 0.262 | no |
80 | 2010 | 73171 | Earth Reborn | 0.261 | yes |
81 | 2017 | 192827 | RUM | 0.259 | no |
82 | 1999 | 47 | Chinatown | 0.258 | no |
83 | 2006 | 22141 | Cleopatra and the Society of Architects | 0.255 | no |
84 | 2001 | 25821 | The Werewolves of Miller's Hollow | 0.253 | no |
85 | 2015 | 170216 | Blood Rage | 0.252 | yes |
86 | 2010 | 65200 | Asteroyds | 0.246 | no |
87 | 2007 | 29937 | König von Siam | 0.246 | no |
88 | 2018 | 259829 | Loser | 0.244 | no |
89 | 2019 | 245655 | The King's Dilemma | 0.243 | yes |
90 | 2018 | 233080 | Book of Dragons | 0.243 | no |
91 | 2005 | 15157 | Amazonas | 0.240 | no |
92 | 2014 | 163412 | Patchwork | 0.238 | no |
93 | 2000 | 558 | Der weiße Lotus | 0.237 | no |
94 | 2019 | 266507 | Clank!: Legacy – Acquisitions Incorporated | 0.237 | no |
95 | 2016 | 195856 | Bloodborne: The Card Game | 0.236 | yes |
96 | 2018 | 247236 | Duelosaur Island | 0.230 | no |
97 | 2017 | 222887 | Twin It! | 0.228 | no |
98 | 2010 | 82702 | Funfair | 0.227 | no |
99 | 2013 | 143693 | Glass Road | 0.226 | no |
100 | 2011 | 94104 | Omen: A Reign of War | 0.226 | yes |
This section contains a variety of visualizations and metrics for assessing the performance of the model(s) during resampling. If you’re not particularly interested in predictive modeling, skip down further to the predictions from the model.
An easy way to examine the performance of classification model is to view a separation plot. We plot the predicted probabilities from the model for every game (from resampling) from lowest to highest. We then overlay a blue line for any game that the user does own. A good classifier is one that is able to separate the blue (games owned by the user) from the white (games not owned by the user), with most of the blue occurring at the highest probabilities (right side of the chart).
We can more formally assess how well each model did in resampling by looking at the area under the receiver operating characteristic curve. A perfect model would receive a score of 1, while a model that cannot predict the outcome will default to a score of 0.5. The extent to which something is a good score depends on the setting, but generally anything in the .8 to .9 range is very good while the .7 to .8 range is perfectly acceptable.
wflow_id | .metric | .estimator | .estimate |
GLM | roc_auc | binary | 0.83 |
Decision Tree | roc_auc | binary | 0.72 |
Another way to think about the model performance is to view its lift, or its ability to detect the positive outcomes over that of a null model. High lift indicates the model can much more quickly find all of the positive outcomes (in this case, games owned or played by the user), while a model with no lift is no better than random guessing. A gains chart is another way to view this.
While we are probably more interested in the lift provided by the models to evaluate their efficacy, we can also explore the optimal cutpoint if we wanted to define a hard threshold for identifying games a user will own vs not own.
The threshold we select depends on how we much we care about false positives (games the model predicts that the user does not own) vs false negatives (games the user owns that the model does not predict). We can toggle threshold to
Finally, we can understand the performance of the model by examining its calibration. If the model assigns a probability of 5%, how often does the outcome actually occur? A well calibrated model is one in which the predicted probabilities reflect the probabilities we would observe in the actual data. We can assess the calibration of a model by grouping its predictions into bins and assessing how often we observe the outcome versus how often our model expects to observe the outcome.
A model that is well calibrated will closely follow the dashed line - its expected probabilities match that of the observed probabilities. A model that consistently underestimates the probability of the event will be over this dashed line, be a while a model that overestimates the probability will be under the dashed line.
What games does the model think aboardgamebarrage is most likely to own that are not in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2018 | 205896 | Rising Sun | 0.948 | no |
2016 | 176083 | Hit Z Road | 0.692 | no |
2014 | 132531 | Roll for the Galaxy | 0.681 | no |
2015 | 175878 | 504 | 0.632 | no |
2016 | 205398 | Citadels | 0.628 | no |
What games does the model think aboardgamebarrage is least likely to own that are in their collection?
Published | ID | Name | Pr(Owned) | Owned |
1876 | 521 | Crokinole | 0.001 | yes |
2016 | 194964 | Mothership: Tabletop Combat | 0.002 | yes |
2013 | 146910 | Wildcatters | 0.003 | yes |
2017 | 201921 | Tiny Epic Quest | 0.003 | yes |
1992 | 327 | Loopin' Louie | 0.003 | yes |
Top 25 games most likely to be owned by the user in each year, highlighting in blue the games that the user has owned.
rank | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
1 | Archipelago | Room 25 | Roll for the Galaxy | 504 | Hit Z Road | Twilight Imperium: Fourth Edition | Rising Sun | Tapestry |
2 | Wiz-War (Eighth Edition) | Ladies & Gentlemen | Black Fleet | Mysterium | Citadels | Gaia Project | New Frontiers | Last Bastion |
3 | Terra Mystica | Glass Road | Illegal | Hemloch: Midnight Edition | Star Wars: Rebellion | The Godfather: Corleone's Empire | The World of SMOG: Rise of Moloch | Western Empires |
4 | The Resistance: Avalon | Impulse | Five Tribes | Mission: Red Planet (Second Edition) | Burke's Gambit | Pandemic Legacy: Season 2 | Everdell | Victorian Masterminds |
5 | Tooth & Nail: Factions | Dungeon Twister: The Card Game | Ultimate Werewolf | Blood Rage | Codenames: Deep Undercover | Hemloch: Dark Promenade | Cosmic Encounter: 42nd Anniversary Edition | Ninja Academy |
6 | Yedo | Παλέρμο: Το Μεγάλο Ξεκαθάρισμα | Splendor | Hordes of Grimoor | Terraforming Mars | Breaking Bad: The Board Game | Loser | Slyville |
7 | Coup | La Boca | Colt Express | Salem 1692 | Akua | Secrets | Book of Dragons | Machi Koro Legacy |
8 | Mafia: Vendetta | Hemloch: Vault of Darkness | Patchwork | Tiny Epic Galaxies | Crazy Karts | Wasteland Express Delivery Service | Duelosaur Island | Era: Medieval Age |
9 | Keyflower | Animals Frightening Night! | Sons of Anarchy: Men of Mayhem | Codenames | Bloodborne: The Card Game | Best of Werewolves of Miller's Hollow | Forsaken Forest | Ravnica: Inquisition |
10 | Exodus: Proxima Centauri | Tash-Kalar: Arena of Legends | The Worst Game Ever | Watson & Holmes | GearSeed | Merchants of Muziris | Newton | Yukon Airways |
11 | Targi | Two Rooms and a Boom | Tiny Epic Kingdoms | Stockpile | Neolithic | Gloomhaven | MeowMeow Mia | The Magnificent |
12 | Love Letter | Fox & Chicken | Deception: Murder in Hong Kong | One Night Revolution | New Angeles | RUM | Railroad Ink: Deep Blue Edition | Omen: Fires in the East |
13 | Divinare | Bruxelles 1893 | One Night Ultimate Werewolf | Raptor | Codenames: Pictures | Twin It! | Exodus: Paris Nouveau | The King's Dilemma |
14 | Libertalia | Patchistory | Imperial Settlers | Keep | Captain Sonar | Tsukiji | Ultimate Werewolf Legacy | Clank!: Legacy – Acquisitions Incorporated |
15 | Space Cadets | BANG! The Dice Game | Hyperborea | Metal Adventures | SYNOD | GYM | Narcos: The Board Game | Aftershock: San Francisco & Venice |
16 | Zombicide | Tomorrow | Pandemic: Contagion | The King Is Dead | Dead Last | Oktoberfest | Shadows: Amsterdam | Unmatched Game System |
17 | The Great Zimbabwe | Blood Bound | HINT | Grand Austria Hotel | Not Alone | Werewords | Fool! | Pandemic: Rapid Response |
18 | Seasons | Nosferatu | AquaSphere | Mafia de Cuba | Heir to the Pharaoh | Downforce | Century: Eastern Wonders | Caylus 1303 |
19 | Dixit Jinx | Stone & Relic | La Granja | El Grande Big Box | Turin Market | Hellapagos | Nyctophobia | Amul |
20 | Android: Netrunner | Cappuccino | Deus | Orphan Black: The Card Game | 75 Gnom' Street | DIG | Fireball Island: The Curse of Vul-Kar | GROWL |
21 | Sky Tango | Crossing | Bucket King 3D | Bastion | Santorini | SPY | Jurassic Park: Danger! | The Last Station |
22 | Robinson Crusoe: Adventures on the Cursed Island | Cinque Terre | Ca$h 'n Guns (Second Edition) | The Fittest | Corrupted Kingdoms | Photosynthesis | Patriots & Redcoats | Three-Dragon Ante: Legendary Edition |
23 | Copycat | Colonialism | Dogs of War | T.I.M.E Stories | Omen: Edge of the Aegean | Century: Spice Road | Lords of Hellas | Silver & Gold |
24 | Clash of Cultures | Concept | Akrotiri | Mombasa | Exceed Fighting System | Dragon Castle | Decrypto | Hidden Panda |
25 | The Last Banquet | Warhammer: Diskwars | Sheriff of Nottingham | Soulfall | Junta: Las Cartas | Smash Up: What Were We Thinking? | The Pirate Republic | Throw Throw Burrito |
This is an interactive table for the model’s predictions for the training set (from resampling).
We’ll validate the model by looking at its predictions for games published in 2020. That is, how well did a model trained on a user’s collection through 2020 perform in predicting games for the user in 2020?
username | outcome | dataset | method | .metric | .estimate |
aboardgamebarrage | owned | validation | GLM | roc_auc | 0.821 |
aboardgamebarrage | owned | validation | Decision Tree | roc_auc | 0.701 |
Table of top 50 games from 2020, highlighting games that the user owns.
Published | ID | Name | Pr(Owned) | Owned |
2020 | 256317 | Guild Master | 0.467 | no |
2020 | 316377 | 7 Wonders (Second Edition) | 0.407 | no |
2020 | 291457 | Gloomhaven: Jaws of the Lion | 0.340 | no |
2020 | 274072 | Omen: Heir to the Dunes | 0.281 | no |
2020 | 243797 | Mezo | 0.273 | yes |
2020 | 318084 | Furnace | 0.229 | no |
2020 | 302889 | Cacti | 0.217 | no |
2020 | 298572 | Cosmic Encounter Duel | 0.213 | no |
2020 | 184267 | On Mars | 0.211 | no |
2020 | 314040 | Pandemic Legacy: Season 0 | 0.180 | no |
2020 | 306481 | Tawantinsuyu: The Inca Empire | 0.170 | no |
2020 | 287033 | Gray Eminence | 0.168 | no |
2020 | 245659 | Vampire: The Masquerade – Vendetta | 0.166 | no |
2020 | 295905 | Cosmic Frog | 0.160 | no |
2020 | 296626 | Sonora | 0.157 | no |
2020 | 313946 | Sandstone | 0.156 | yes |
2020 | 313817 | Hello Neighbor: The Secret Neighbor Party Game | 0.151 | no |
2020 | 233262 | Tidal Blades: Heroes of the Reef | 0.151 | no |
2020 | 296151 | Viscounts of the West Kingdom | 0.151 | no |
2020 | 246900 | Eclipse: Second Dawn for the Galaxy | 0.148 | no |
2020 | 319966 | The King Is Dead: Second Edition | 0.143 | no |
2020 | 298371 | Wild Space | 0.120 | no |
2020 | 299607 | Capital Lux 2: Generations | 0.119 | no |
2020 | 256999 | Project: ELITE | 0.119 | no |
2020 | 315060 | Unmatched: Buffy the Vampire Slayer | 0.114 | no |
2020 | 296892 | Sacred Rites | 0.112 | no |
2020 | 282171 | Trial by Trolley | 0.110 | no |
2020 | 311927 | Long Live the King: A Game of Secrecy and Subterfuge | 0.107 | no |
2020 | 282922 | Windward | 0.105 | no |
2020 | 229782 | Roland Wright: The Dice Game | 0.104 | no |
2020 | 307997 | Insider Black | 0.104 | no |
2020 | 245658 | Unicorn Fever | 0.103 | no |
2020 | 300322 | Hallertau | 0.101 | no |
2020 | 295687 | Trust Me, I'm a Doctor | 0.098 | no |
2020 | 284777 | Unmatched: Jurassic Park – InGen vs Raptors | 0.098 | no |
2020 | 301767 | Mysterium Park | 0.096 | no |
2020 | 282081 | The Zorro Dice Game | 0.095 | no |
2020 | 277927 | Bites | 0.093 | no |
2020 | 312762 | The Joker | 0.092 | no |
2020 | 295646 | Spyfest | 0.090 | no |
2020 | 301716 | Glasgow | 0.089 | no |
2020 | 257001 | Munchkin Dungeon | 0.088 | no |
2020 | 303051 | Godzilla: Tokyo Clash | 0.084 | no |
2020 | 256940 | Krosmaster: Blast | 0.081 | no |
2020 | 296512 | The Game: Quick & Easy | 0.081 | no |
2020 | 316412 | The LOOP | 0.080 | no |
2020 | 299592 | Beez | 0.080 | no |
2020 | 315631 | Santorini: New York | 0.076 | no |
2020 | 279198 | Tungaru | 0.075 | no |
2020 | 270685 | Capone: The Business of Prohibition | 0.075 | no |
We can then refit our model to the training and validation set in order to predict all upcoming games for the user.
Examine the top 100 upcoming games, highlighting in blue ones the user already owns.
Rank | Published | ID | Name | Pr(Owned) | Owned |
1 | 2021 | 333348 | Dirge: The Rust Wars | 0.562 | no |
2 | 2021 | 285967 | Ankh: Gods of Egypt | 0.538 | no |
3 | 2021 | 316287 | Quest | 0.328 | no |
4 | 2022 | 302887 | Bronze Age | 0.314 | no |
5 | 2022 | 240980 | Blood on the Clocktower | 0.268 | no |
6 | 2021 | 338980 | Eastern Empires | 0.242 | no |
7 | 2023 | 349793 | Age of Rome | 0.217 | no |
8 | 2021 | 330608 | Cryo | 0.207 | no |
9 | 2021 | 340466 | Unfathomable | 0.164 | no |
10 | 2022 | 283137 | Human Punishment: The Beginning | 0.159 | no |
11 | 2022 | 271601 | Feed the Kraken | 0.155 | no |
12 | 2022 | 338067 | 6: Siege – The Board Game | 0.142 | no |
13 | 2021 | 339790 | Cocktail | 0.138 | no |
14 | 2021 | 292899 | Tribune | 0.136 | no |
15 | 2022 | 310873 | Carnegie | 0.128 | no |
16 | 2022 | 353470 | Star Wars: Jabba's Palace – A Love Letter Game | 0.123 | no |
17 | 2021 | 331685 | Hit the Silk! | 0.121 | no |
18 | 2021 | 332944 | Sobek: 2 Players | 0.120 | no |
19 | 2022 | 332393 | Bridge City Poker | 0.112 | no |
20 | 2021 | 343696 | Dune: Betrayal | 0.111 | no |
21 | 2021 | 342848 | World of Warcraft: Wrath of the Lich King | 0.104 | no |
22 | 2021 | 344258 | That Time You Killed Me | 0.103 | no |
23 | 2021 | 273330 | Bloodborne: The Board Game | 0.101 | no |
24 | 2022 | 295770 | Frosthaven | 0.101 | no |
25 | 2022 | 315610 | Massive Darkness 2: Hellscape | 0.100 | no |
26 | 2021 | 331635 | Kameloot | 0.097 | no |
27 | 2021 | 333553 | For the King (and Me) | 0.095 | no |
28 | 2021 | 306202 | Philosophia: Floating World | 0.094 | no |
29 | 2021 | 311920 | Ultimate Werewolf: Extreme | 0.094 | no |
30 | 2021 | 221298 | NewSpeak | 0.093 | no |
31 | 2021 | 332386 | Brew | 0.092 | no |
32 | 2021 | 322014 | All-Star Draft | 0.092 | no |
33 | 2021 | 291572 | Oath: Chronicles of Empire and Exile | 0.089 | no |
34 | 2021 | 328286 | Mission ISS | 0.089 | no |
35 | 2021 | 266448 | Imperium: The Contention | 0.089 | no |
36 | 2021 | 308989 | Bristol 1350 | 0.088 | no |
37 | 2021 | 328871 | Terraforming Mars: Ares Expedition | 0.088 | no |
38 | 2022 | 320718 | Hidden Leaders | 0.087 | no |
39 | 2022 | 308028 | Drop Drive | 0.085 | no |
40 | 2021 | 337262 | Fangs | 0.085 | no |
41 | 2021 | 314491 | Meadow | 0.085 | no |
42 | 2022 | 335764 | Unmatched: Battle of Legends, Volume Two | 0.084 | no |
43 | 2021 | 286751 | Zombicide: 2nd Edition | 0.084 | no |
44 | 2022 | 318838 | Quests & Cannons: The Risen Islands | 0.084 | no |
45 | 2021 | 308566 | Nova Lux | 0.082 | no |
46 | 2021 | 275557 | The Last Bottle of Rum | 0.080 | no |
47 | 2022 | 284778 | Unmatched: Jurassic Park – Dr. Sattler vs. T. Rex | 0.079 | no |
48 | 2021 | 257435 | Brick & Mortar | 0.077 | no |
49 | 2021 | 331549 | MiniQuest Adventures | 0.076 | no |
50 | 2022 | 341945 | La Granja: Deluxe Master Set | 0.074 | no |
51 | 2021 | 322339 | Hanamikoji: Geisha's Road | 0.073 | no |
52 | 2022 | 352201 | Skull Canyon: Ski Fest | 0.073 | no |
53 | 2021 | 356907 | Mascarade (second edition) | 0.073 | no |
54 | 2021 | 337389 | Snakesss | 0.073 | no |
55 | 2022 | 295374 | Long Shot: The Dice Game | 0.071 | no |
56 | 2021 | 249277 | Brazil: Imperial | 0.071 | no |
57 | 2022 | 317511 | Tindaya | 0.070 | no |
58 | 2022 | 343900 | Senjutsu: Battle For Japan | 0.069 | no |
59 | 2021 | 329714 | Dreadful Circus | 0.069 | no |
60 | 2021 | 320069 | Tavern Tales: Legends of Dungeon Drop | 0.069 | no |
61 | 2022 | 331106 | The Witcher: Old World | 0.068 | no |
62 | 2021 | 316343 | Capital Lux 2: Pocket | 0.068 | no |
63 | 2021 | 335541 | We Care: a Grizzled Game | 0.068 | no |
64 | 2021 | 316625 | Cafe Chaos | 0.068 | no |
65 | 2021 | 328569 | Mint Bid | 0.068 | no |
66 | 2022 | 354254 | Voices In My Head | 0.067 | no |
67 | 2021 | 295947 | Cascadia | 0.067 | no |
68 | 2021 | 286439 | Import / Export: Definitive Edition | 0.066 | no |
69 | 2021 | 341048 | Free Ride | 0.066 | no |
70 | 2023 | 315727 | Last Light | 0.065 | no |
71 | 2021 | 318709 | For Sale Autorama | 0.064 | no |
72 | 2022 | 275215 | Namiji | 0.063 | no |
73 | 2022 | 319807 | Shogun no Katana | 0.063 | no |
74 | 2021 | 340677 | Bad Company | 0.062 | no |
75 | 2022 | 340672 | Council of 12 | 0.062 | no |
76 | 2022 | 339592 | Sheep in Disguise | 0.062 | no |
77 | 2021 | 346950 | Into the Blue | 0.061 | no |
78 | 2021 | 344408 | Full Throttle! | 0.061 | no |
79 | 2021 | 329450 | Equinox | 0.061 | no |
80 | 2021 | 342942 | Ark Nova | 0.060 | no |
81 | 2021 | 291859 | Riftforce | 0.060 | no |
82 | 2021 | 340420 | Throw Throw Avocado | 0.060 | no |
83 | 2021 | 313262 | Shamans | 0.059 | no |
84 | 2021 | 320136 | Naruto: Ninja Arena | 0.059 | no |
85 | 2021 | 239175 | Shiver Me Timbers | 0.058 | no |
86 | 2021 | 330036 | Great Plains | 0.058 | no |
87 | 2023 | 347909 | Rogue Angels: Legacy of the Burning Suns | 0.058 | no |
88 | 2022 | 346199 | A Game of Thrones: B'Twixt | 0.057 | no |
89 | 2022 | 266064 | Trudvang Legends | 0.057 | no |
90 | 2022 | 344050 | Dubious | 0.057 | no |
91 | 2021 | 283387 | Rocketmen | 0.055 | no |
92 | 2023 | 337627 | Voidfall | 0.055 | no |
93 | 2021 | 290236 | Canvas | 0.055 | no |
94 | 2021 | 314032 | Levitation: Masters of Magic | 0.055 | no |
95 | 2021 | 326804 | Rorschach | 0.054 | no |
96 | 2021 | 329670 | Pandemic: Hot Zone – Europe | 0.054 | no |
97 | 2022 | 299594 | Megapulse | 0.054 | no |
98 | 2021 | 275061 | Rulebenders | 0.053 | no |
99 | 2022 | 288080 | Dice Realms | 0.053 | no |
100 | 2021 | 306321 | Night of the Ninja | 0.053 | no |